Mining Biomedical Text, Images and Visual Features for Information Retrieval provides the reader with a broad coverage of the concepts, themes, and instrumentalities of the important and evolving area of biomedical text, images, and visual features towards information retrieval. It aims to encourage an even wider adoption of IR methods for assisting in problem-solving and to stimulate research that may lead to additional innovations in this area of research. The book discusses topics such as internet of things for health informatics; data privacy; smart healthcare; medical image processing; 3D medical images; evolutionary computing; deep learning; medical ontology; linguistic indexing; lexical analysis; and domain specific semantic categories in biomedical applications. It is a valuable resource for researchers and graduate students who are interested to learn more about data mining techniques to improve their research work.
Mining Biomedical Text, Images and Visual Features for Information Retrieval provides the reader with a broad coverage of the concepts, themes, and instrumentalities of the important and evolving area of biomedical text, images, and visual features towards information retrieval. It aims to encourage an even wider adoption of IR methods for assisting in problem-solving and to stimulate research that may lead to additional innovations in this area of research. The book discusses topics such as internet of things for health informatics; data privacy; smart healthcare; medical image processing; 3D medical images; evolutionary computing; deep learning; medical ontology; linguistic indexing; lexical analysis; and domain specific semantic categories in biomedical applications. It is a valuable resource for researchers and graduate students who are interested to learn more about data mining techniques to improve their research work.
Part I: IoT for Biomedical and Health Informatics
1. Introduction to IoT and Health Informatics
2. IoT system architectures in healthcare
3. Computational Intelligence in IoT Healthcare
4. Data Privacy in IoT E-health
5. IoT big data analytics in the healthcare industry.
6. Methodical IoT Based Information System in Healthcare
Industry.
7. IoT for Smart Healthcare monitoring System
Part II: Computational Intelligence for Medical Image
Processing
8. Computational Intelligence approaches in Biomedical image
Processing
9. Distributed 3-D Medical Image Registration Using Intelligent
Agents
10. Image Segmentation and Parameterization for Automatic
Diagnostics
11. Computational Intelligence on Medical Imaging with Artificial
Neural Networks
12. Evolutionary Computing and Its Use in Medical Imaging
13. Image Informatics for Clinical and Preclinical Biomedical
Analysis
14. Topic Extractions (in Psychology)
15. Deep Learning in Medical Image Analysis
16. Automatic Segmentation of Multiple Organs on CT Images by Using
Deep Learning Approaches
17. Medical Image Synthesis using Deep Learning
18. Medical Image Mining Using Data Mining Techniques
19. Biomedical Image Characterization and Radio genomics Using
Machine Learning Techniques
Part III: Biomedical Natural Language Processing
20. Medical Ontology for text Categorization System
21. Biomedical terminologies resources for Information
Retrieval
22. Image retrieval and Linguistic Indexing
23. Translation of Biomedical terms Using inferring rewriting
rules
24. Lexical Analysis of Biomedical Ontologies
25. Word Sense Disambiguation in biomedical applications
26. Domain Specific Semantic Categories in Biomedical applications
Sujata Dash holds the position of Professor at the Information
Technology School of Engineering and Technology, Nagaland
University, Dimapur Campus, Nagaland, India, bringing more than
three decades of dedicated service in teaching and mentoring
students. She has been honoured with the prestigious Titular
Fellowship from the Association of Commonwealth Universities,
United Kingdom. As a testament to her global contributions, she
served as a visiting professor in the Computer Science Department
at the University of Manitoba, Canada. With a prolific academic
record, she has authored over 200 technical papers published in
esteemed international journals, and conference proceedings, and
edited book chapters by reputed publishers Serving as a reviewer
and Associate Editor for approximately 15 international
journals.
Subhendu Kumar Pani received his Ph.D. from Utkal University
Odisha, India. He has more than 16 years of teaching and research
experience. His research interests include data mining, big data
analysis, web data analytics, fuzzy decision making and
computational intelligence. He is a fellow in SSARSC and life
member in IE, ISTE, ISCA, OBA.OMS, SMIACSIT, SMUACEE, CSI.
Professor dos Santos is creator and developer of innovative
healthcare solutions for diagnosis and treatment using Artificial
Intelligence. Applications in digital epidemiology, neuroscience,
diagnostic imaging, diagnosis by signs, diagnosis by laboratory
tests, health informatics and bioinformatics. Founder of the Ada
Lovelace Association. Leader of the Research Group on Biomedical
Computing at UFPE. Enthusiast of social entrepreneurship and
innovation in health. Before joining UAB, Dr. Chen was the founding
director of the Indiana Center for Systems Biology and Personalized
Medicine at Indiana University and a tenured faculty member at
Indiana University School of Informatics and Purdue University
Computer Science Department. Dr. Chen has over 20 years of research
and development experience in biological data mining, systems
biology, and translational informatics in both Academia and the
industry. He has over 150 peer-reviewed publications and presented
worldwide on topics related to biocomputing, bioinformatics, and
data sciences in life sciences. He was elected as the
President-elect of the Midsouth Computational Biology and
Bioinformatics Society (MCBIOS) in 2019. He also serves on the
editorial boards of BMC Bioinformatics, Journal of American Medical
Informatics Association (JAMIA), and Personalized Medicine.
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